» Articles » PMID: 19717802

Describing and Modeling Workflow and Information Flow in Chronic Disease Care

Overview
Date 2009 Sep 1
PMID 19717802
Citations 62
Authors
Affiliations
Soon will be listed here.
Abstract

Objectives: The goal of the study was to develop an in-depth understanding of work practices, workflow, and information flow in chronic disease care, to facilitate development of context-appropriate informatics tools.

Design: The study was conducted over a 10-month period in three ambulatory clinics providing chronic disease care. The authors iteratively collected data using direct observation and semi-structured interviews.

Measurements: The authors observed all aspects of care in three different chronic disease clinics for over 150 hours, including 157 patient-provider interactions. Observation focused on interactions among people, processes, and technology. Observation data were analyzed through an open coding approach. The authors then developed models of workflow and information flow using Hierarchical Task Analysis and Soft Systems Methodology. The authors also conducted nine semi-structured interviews to confirm and refine the models.

Results: The study had three primary outcomes: models of workflow for each clinic, models of information flow for each clinic, and an in-depth description of work practices and the role of health information technology (HIT) in the clinics. The authors identified gaps between the existing HIT functionality and the needs of chronic disease providers.

Conclusions: In response to the analysis of workflow and information flow, the authors developed ten guidelines for design of HIT to support chronic disease care, including recommendations to pursue modular approaches to design that would support disease-specific needs. The study demonstrates the importance of evaluating workflow and information flow in HIT design and implementation.

Citing Articles

Interventions to Mitigate EHR and Documentation Burden in Health Professions Trainees: A Scoping Review.

Levy D, Rossetti S, Rossetti S, Brandt C, Brandt C, Melnick E Appl Clin Inform. 2024; 16(1):111-127.

PMID: 39366661 PMC: 11798655. DOI: 10.1055/a-2434-5177.


Workflow analysis of breast cancer treatment decision-making: challenges and opportunities for informatics to support patient-centered cancer care.

Salwei M, Reale C JAMIA Open. 2024; 7(2):ooae053.

PMID: 38911330 PMC: 11192055. DOI: 10.1093/jamiaopen/ooae053.


Patient-centered clinical decision support challenges and opportunities identified from workflow execution models.

Sittig D, Boxwala A, Wright A, Zott C, Gauthreaux N, Swiger J J Am Med Inform Assoc. 2024; 31(8):1682-1692.

PMID: 38907738 PMC: 11258405. DOI: 10.1093/jamia/ocae138.


Improving the mental health care process in response to Covid-19 pandemic: The case of a penitentiary mental health division.

Nuzzi A, Latorre V, Semisa D, Scozzi B PLoS One. 2023; 18(10):e0293492.

PMID: 37903102 PMC: 10615294. DOI: 10.1371/journal.pone.0293492.


The Vinyasa Tool for mHealth Solutions: Supporting Human-Centered Design in Nascent Digital Health Ecosystems.

Thomas V, Kalidindi B, Waghmare A, Bhatia A, Raj T, Balsari S JMIR Form Res. 2023; 7:e45250.

PMID: 37607881 PMC: 10580130. DOI: 10.2196/45250.


References
1.
Shaw N, Mador R, Ho S, Mayes D, Westbrook J, Creswick N . Understanding the impact on intensive care staff workflow due to the introduction of a critical care information system: a mixed methods research methodology. Stud Health Technol Inform. 2009; 143:186-91. View

2.
Zai A, Grant R, Estey G, Lester W, Andrews C, Yee R . Lessons from implementing a combined workflow-informatics system for diabetes management. J Am Med Inform Assoc. 2008; 15(4):524-33. PMC: 2442271. DOI: 10.1197/jamia.M2598. View

3.
Johnson K, FitzHenry F . Case report: activity diagrams for integrating electronic prescribing tools into clinical workflow. J Am Med Inform Assoc. 2006; 13(4):391-5. PMC: 1513671. DOI: 10.1197/jamia.M2008. View

4.
Ventres W, Kooienga S, Vuckovic N, Marlin R, Nygren P, Stewart V . Physicians, patients, and the electronic health record: an ethnographic analysis. Ann Fam Med. 2006; 4(2):124-31. PMC: 1467009. DOI: 10.1370/afm.425. View

5.
Unertl K, Weinger M, Johnson K . Applying direct observation to model workflow and assess adoption. AMIA Annu Symp Proc. 2007; :794-8. PMC: 1839698. View